Data silos have long been one of healthcare’s biggest setbacks. As much as the industry is embracing the power of new technologies and more connected systems, these tools can’t work without the right data – extensive longitudinal, primary source real-world data (RWD) – informing them.
RWD is a cornerstone of healthcare. It’s the foundation that has allowed our industry to deliver life-saving vaccines to patients, close critical access gaps, and continue to advance in every aspect, from a faster check-in process at the doctor’s office to developing a groundbreaking treatment for a rare disease.
However, this level of impact has traditionally occurred after significant time collecting, standardizing, and combining datasets. Imagine what could happen when the long-standing data siloes of healthcare are broken; when data is securely and appropriately shared at scale to more rapidly inform advancements throughout the care journey.
Creating more data connections
Our industry must continue to make significant progress in data management and governance to overcome the silos and fragmentation that exist, while upholding a commitment to protect patient data. It’s a fine balance to establish more robust data connections, unlock the value of data, and maintain privacy; focusing too heavily on privacy can limit the value gained from analyses and connected datasets, while focusing on value alone can introduce privacy risks.
However, it’s certainly possible. In the financial services industry, for example – where privacy is equally critical – consumers can make faster, more informed decisions about their investments thanks to the innovations powered by stronger data networks. Patients expect a similar experience for their healthcare. They want to be more informed about their conditions and treatment plans, and they expect their providers to have relevant data about them at the ready.
Establishing deeper, further-reaching data access and connections requires a combination of policy evolution, increased partnerships across the healthcare ecosystem, and more widespread adoption of cloud-based data platforms. The data that has historically sat in its own application or warehouse, or buried deep in clinical notes, is increasingly coming together in a thoughtful, purposeful way – and it’s the organizations who lean in first who will have the most insights to gain.
The value of bigger, more comprehensive datasets
As the industry continues to advance its utilization and integration of disparate data sources, we will continue to see accelerating progress in clinical trials, oncology care, opioid use, and policy development.
Historically, 80% of clinical trials have failed to meet enrollment deadlines, often due to challenges in finding the appropriate patients and confirming their trial eligibility. RWD can help trial sponsors find the patients they need faster – to understand their conditions, if they fit trial requirements, where they are, and how to engage them. This opens the door for more patients to gain new treatment options during the trial, and as more trials are completed successfully, the benefits can have profound ripple effects for thousands of patients beyond the trial participants.
In oncology care, earlier detection can help save lives. Breast cancer is the second leading cause of cancer death for women, but early detection boosts five-year survival rates to an average of 99%. However, screening rates are alarmingly low for some populations – consistently lowest among women with Medicaid and additional disparities exist across geography and age. Understanding these disparities, and the characteristics of the women going without screenings, is a critical step in increasing screening rates to ultimately help improve breast cancer outcomes.
Similarly, RWD can help healthcare teams better combat the opioid crisis, which continues to be a public health issue in the U.S. Though overdose deaths decreased 26.9% from 2023 to 2024, with opioid overdoses specifically decreasing by 36.5%, there is still much work to be done to address opioid use disorder (OUD). A closer look at OUD data reveals alarming disparities in care by insurance type, sex, age, and location – giving providers, health plans, and policymakers the insights they need to further address this far-reaching challenge.
Beyond new trials and specific conditions, RWD can also shed light on healthcare spending and resource utilization, helping the entire care ecosystem operate more effectively for key players and the patients they serve. When comparing Medicare Advantage (MA) to Fee-for-Service (FFS), for example, older adults who choose MA over FFS enter Medicare with an 11% higher clinical risk yet generate 11% lower total costs than clinically and socio-demographically similar FFS enrollees.
The AI (cause and) effect
We can’t talk about healthcare data without talking about AI – and we’re only at the beginning of understanding what AI can do to advance care access, treatments, and outcomes. Even in the next 5 years, the role of AI in healthcare will be something we don’t recognize; it has the potential to make a truly profound impact given the rapid pace of advancement in AI capabilities.
Today, that means investing in more robust, high-quality, and connected datasets while continuing to unlock the power of data with the tools we have available. These advancements drive progress in the overall healthcare ecosystem by eliminating the data barriers that may have historically held us back. More sophisticated AI models will continue to emerge and will be applied on top of these datasets to derive even more meaningful insights with increasing speed.
As this transformation unfolds, however, the expertise and compassion that can only come from human interaction is critical, especially when it comes to patient care. By harnessing the combined power of people, connected data, and robust models, we can better serve all patients, improve care outcomes, and make the entire care system operate more efficiently.
Ed Chidsey
Ed Chidsey serves as the President of Inovalon's Insights business unit, leading the Company's provision of data solutions to organizations throughout the healthcare ecosystem, empowering the application of unique data to deliver better outcomes and economics. In this role, Mr. Chidsey leads and is responsible for the management, product portfolio, sales, customer success, operations, and overall performance of the Insights business.
Prior to his role at Inovalon, Mr. Chidsey was Senior Vice President and global head of the Data, Valuations & Analytics business within S&P Global's Market Intelligence division. In that capacity, he had full responsibility for a $1 billion revenue portfolio covering cross-asset class Market Data, Reference Data, Valuation, and Company Information Services across public, OTC, and private markets.
Mr. Chidsey joined S&P Global after its merger with IHS Markit in 2022, where he had been since 2007 and was a Partner with responsibility for the Information Services business. He was a member of the senior management team that drove rapid growth of Markit as a private company, leading to a Nasdaq listing in 2014 and the merger with IHS in 2016.
Mr. Chidsey holds a Master of Business Administration from Columbia University and holds a Bachelor of Science in Mechanical Engineering from Union College.
